
Later [1]} proved a lower bound for the methods that is involving nuclear norm minimization, and result could be presented as below:
 [1]}
Suppose that M is an \(n_1 \times n_2\)  sized matrix with rank \(r\) , and \(\mu _0 \)  is larger or equal than one.
Then under the uniform sampling observation process, there are infinitely with the fixed entry values given that   \( 0 < \delta < 1/2 \)    and
\(m < (1-\epsilon ) \mu _0 \mathrm {max}(n_1,n_2) r \log { \frac{n}{2\delta } }\) 
